Global change differentially modulates physiological plasticity of tropical reef-building corals
Last run on 29 June 2021
Principal component analyses
Methods:
Principal component analysis (PCA) (function prcomp) of scaled and centered physiological parameters (host carbohydrate, host lipid, host protein, algal symbiont chlorophyll a, algal symbiont cell density, holobiont calcification rate as previously for the same samples in Bove et al (2019)) were employed to assess the relationship between physiological parameters and treatment conditions for each coral species. Main effects (temperature, pCO2, reef environment) were evaluated with PERMANOVA using the adonis2 function (vegan package; version 2.5.7 (Oksanen et al., 2020)).
Siderastrea siderea
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = sid_pca_df ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 61072 0.20845 8.1535 0.0006662 ***
## ftemp 1 7471 0.02550 2.9922 0.0912725 .
## reef 1 24705 0.08432 9.8948 0.0013324 **
## Residual 80 199740 0.68174
## Total 85 292988 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Pseudodiploria strigosa
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = dip_pca_df ~ reef + ftemp + fpco2, data = p_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## reef 1 97850 0.08659 14.2890 0.0006662 ***
## ftemp 1 515604 0.45625 75.2935 0.0006662 ***
## fpco2 3 30444 0.02694 1.4819 0.2365090
## Residual 71 486202 0.43023
## Total 76 1130099 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Porites astreoides
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = por_pca_df ~ reef + ftemp + fpco2, data = a_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## reef 1 157 0.00111 0.1138 0.7415057
## ftemp 1 25414 0.17971 18.4700 0.0006662 ***
## fpco2 3 30537 0.21594 7.3978 0.0006662 ***
## Residual 62 85309 0.60325
## Total 67 141417 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure 1
Figure 1. Principal component analysis (PCA) of all coral holobiont physiological parameters for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides after 93 days of exposure to different temperature and pCO2 treatments. PCAs in the top row are depicted by temperature treatment for each species (28\(^\circ\) C blue; 31\(^\circ\) C red) and the bottom row of PCAs are depicted by pCO2 for each species (300 \(\mu\)atm light purple; 420 \(\mu\)atm dark purple; 680 \(\mu\)atm light orange; 3290 \(\mu\)atm dark orange). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure 4
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = all_pca_df ~ fpco2 + ftemp + reef + species + ftemp:species + fpco2:species + reef:species, data = all_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 149393 0.03848 8.2405 0.0006662 ***
## ftemp 1 17313 0.00446 2.8650 0.0932712 .
## reef 1 58058 0.01496 9.6075 0.0046636 **
## species 2 1642613 0.42313 135.9102 0.0006662 ***
## ftemp:species 2 553351 0.14254 45.7844 0.0006662 ***
## fpco2:species 6 90865 0.02341 2.5061 0.0239840 *
## reef:species 2 77259 0.01990 6.3924 0.0039973 **
## Residual 214 1293204 0.33312
## Total 231 3882055 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure 4. Principal component analysis (PCA) comparing the coral holobiont of all three species at the end of the experiment depicted by (A) species, (B) pCO2 treatment, and (C) temperature treatment. Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Results
Principal component analysis
Two principal components (PCs) explained approximately 66% of the variance in physiological responses of the S. siderea holobiont to ocean acidification and warming treatments (Figure 1A). PC1 was driven by differences in algal symbiont physiology (chlorophyll a, cell density), while PC2 represented an inverse relationship between host energy reserves (lipid, protein, carbohydrate) and calcification rates and color intensities. Overall, lower pCO2 and temperature resulted in higher S. siderea holobiont physiology (Figure 1A). Treatment pCO2 predominantly drove S. siderea physiological responses (p = 7e-04; Table S2), while temperature and reef environment did not explain as much variation in physiological responses (p = 0.09 and p = 0.001, respectively; Table S2; Figure S1A).
For P. strigosa, 74% of the variance in the holobiont responses to treatments was explained by two PCs (Figure 1B). PC1 explained most of the variation of physiological parameters with the exception of host lipid content, which was represented in PC2. Holobiont physiology of P. strigosa was reduced under warming (p = 7e-04; Table S2) and in offshore samples (p = 7e-04; Table S2; Figure S1B), however, pCO2 did not clearly impact holobiont physiology (Figure 1B; p = 0.2; Table S2).
For P. astreoides, the first two PCs explained about 59% of the total variance in holobiont response to treatment (Figure 1C). Samples separated most clearly along PC1 driven primarily by calcification rate and algal symbiont density, while PC2 exhibited an inverse relationship between host total carbohydrate and color intensity. Overall, lower pCO2 drove higher P. astreoides holobiont physiology, while elevated temperature resulted in greater holobiont physiology (Figure 1C). Temperature (p = 7e-04; Table S2) and pCO2 (p = 7e-04; Table S2) clearly altered P. astreoides holobiont physiology, while reef environment was not significant (p = 0.7; Table S2; Figure S1C).
Species differences in coral holobiont physiology
The first two PCs of the combined holobiont physiology explained about 62% of the total variance across samples (Figure 4). In general, fragments of S. siderea contained higher chlorophyll a content, host carbohydrate, and host lipid content, while P. strigosa fragments typically had greater host protein content accompanied by higher calcification rates, and fragments of P. astreoides were differentiated by their high symbiont densities (Figure 4A; Table S5). Despite being different coral species, coral holobiont physiology exhibited similar physiological responses to pCO2 and temperature treatments (Figure 4B, 4C; Table S5). As pCO2 or temperature increased, coral holobiont physiology was more constrained and exhibited convergent physiological responses under stress. Furthermore, corals from the inshore reef environment exhibited more constrained physiology than their offshore counterparts (Figure S7; Table S5).
Correlation assessments
Methods:
Correlations of all physiological parameters were assessed to determine the relationships between parameters within each species. The Pearson correlation coefficient (R2) of each comparison was calculated using the corrgram package (version 1.13 (Wright, 2018)) and the significance was calculated using the cor.test function. These relationships were then visualized through simple scatterplots.
Figure 2
Figure 2. Coral holobiont physiological parameter scatter plots (top) and correlation matrices (bottom) for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides showing pairwise comparisons of within each species. Scatter plots of each pairwise combination of physiological parameters are displayed on the top with temperature treatment depicted by shape (28\(^\circ\)C closed points; 31\(^\circ\)C open points) and pCO2 treatment depicted by color (pre industrial [300 \(\mu\)atm], light purple; current day [420 \(\mu\)atm], dark purple; end-of-century [680 \(\mu\)atm], light orange; extreme [3290 \(\mu\)atm], dark orange). Strengths of the correlations (R2 via Pearson correlation coefficients) between each pairwise combination of physiological parameters are indicated by darker shades of blue on the bottom with significance depicted by asterisks according to significance level (* p < 0.05; ** p < 0.01; *** p < 0.001). R2 and significance levels correspond to the scatter plot at the intersection between two physiological parameters.
Results
Correlations of physiological parameters
Coral holobiont physiological parameters were generally positively correlated with one another within each of the three species. Correlations between S. siderea holobiont physiological parameters identified 15 significant relationships out of all 21 possible comparisons (Figure 2A). Of those significant correlations, six resulted in a Pearson’s correlation coefficient (R2) equal to or greater than 0.5, with the strongest relationship identified between symbiont density and chlorophyll a (R2 = 0.72).
All pairwise physiological parameters were significantly correlated with one another in P. strigosa and, of those, 15 correlations exhibit moderate (R2 > 0.50) positive relationships (Figure 2B). Notably, the two strongest correlations were host carbohydrate vs. host protein (R2 = 0.70) and host carbohydrate vs. chlorophyll a (R2 = 0.76).
Compared to both S. siderea and P. strigosa, fewer physiological traits were significantly (p < 0.05) correlated with one another in P. astreoides (12 significant out of 21 total comparisons; Figure 2C). Of the significant correlations, only two pairwise comparisons resulted in a Pearson’s correlation coefficient greater than 0.5: chlorophyll a vs. color intensity (R2 = 0.57) and host carbohydrate vs. host protein (R2 = 0.68).
Plasticity analyses
Methods:
Physiological plasticity of each experimental fragment was calculated for each species using all seven PCs calculated above as the distance between an experimental fragment and the control (420 \(\mu\)atm; 28\(^\circ\)C) fragment from that same colony. The effects of treatment (pCO2 and temperature) and natal reef environment on calculated distances were assessed using generalized linear mixed effects models (function lmer) with a Gamma distribution and log-link and a random effect for colony. The best-fit model was selected as the model with the lowest AIC for each species (Table S1). Because only a total of five colonies of P. strigosa remained in the control treatment at the end of the experiment (Noffshore = 3, Ninshore = 2), these samples were pooled across reef environments for this analysis. All figures and statistical analyses were carried out in R version 3.6.3 (R Core Team, 2018) and the accompanying data and code can be freely accessed on GitHub () and Zenodo (DOI here when close to finished).
Siderastrea siderea
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: Gamma ( log )
## Formula: dist ~ reef * fpco2 + ftemp + (1 | colony)
## Data: sid_dist
##
## AIC BIC logLik deviance df.resid
## 218.8 243.5 -98.4 196.8 59
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.99957 -0.62958 -0.09185 0.40989 2.93911
##
## Random effects:
## Groups Name Variance Std.Dev.
## colony (Intercept) 0.03567 0.1889
## Residual 0.09609 0.3100
## Number of obs: 70, groups: colony, 11
##
## Fixed effects:
## Estimate Std. Error t value Pr(>|z|)
## (Intercept) 1.085047 0.172255 6.299 2.99e-10 ***
## reefN -0.058293 0.247860 -0.235 0.81406
## fpco2420 0.334631 0.172672 1.938 0.05263 .
## fpco2680 0.209598 0.130838 1.602 0.10916
## fpco23290 0.418697 0.132009 3.172 0.00152 **
## ftemp31 0.003138 0.076026 0.041 0.96708
## reefN:fpco2420 -0.703806 0.238723 -2.948 0.00320 **
## reefN:fpco2680 -0.409193 0.196622 -2.081 0.03742 *
## reefN:fpco23290 -0.278200 0.191371 -1.454 0.14602
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) reefN fp2420 fp2680 f23290 ftmp31 rN:242 rN:268
## reefN -0.671
## fpco2420 -0.304 0.252
## fpco2680 -0.459 0.325 0.468
## fpco23290 -0.446 0.320 0.475 0.611
## ftemp31 -0.159 -0.038 -0.275 -0.041 -0.069
## rfN:fpc2420 0.244 -0.352 -0.678 -0.331 -0.331 0.034
## rfN:fpc2680 0.310 -0.438 -0.303 -0.664 -0.404 -0.004 0.456
## rfN:fp23290 0.309 -0.449 -0.324 -0.421 -0.689 0.035 0.466 0.572
Pseudodiploria strigosa
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: Gamma ( log )
## Formula: dist ~ fpco2 + ftemp + (1 | colony)
## Data: dip_dist
##
## AIC BIC logLik deviance df.resid
## 97.5 104.8 -42.7 85.5 19
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.70079 -0.72697 0.05779 0.77668 2.01138
##
## Random effects:
## Groups Name Variance Std.Dev.
## colony (Intercept) 0.007898 0.08887
## Residual 0.137879 0.37132
## Number of obs: 25, groups: colony, 5
##
## Fixed effects:
## Estimate Std. Error t value Pr(>|z|)
## (Intercept) 1.27912 0.14767 8.662 <2e-16 ***
## fpco2680 -0.33844 0.19338 -1.750 0.0801 .
## fpco23290 -0.05892 0.18739 -0.314 0.7532
## ftemp31 0.22671 0.17289 1.311 0.1898
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) fp2680 f23290
## fpco2680 -0.579
## fpco23290 -0.578 0.484
## ftemp31 -0.334 0.066 0.012
Porites astreoides
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: Gamma ( log )
## Formula: dist ~ fpco2 + ftemp + (1 | colony)
## Data: por_dist
##
## AIC BIC logLik deviance df.resid
## 140.4 154.4 -63.2 126.4 47
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.6588 -0.5857 -0.1014 0.5424 2.2086
##
## Random effects:
## Groups Name Variance Std.Dev.
## colony (Intercept) 0.03732 0.1932
## Residual 0.05675 0.2382
## Number of obs: 54, groups: colony, 11
##
## Fixed effects:
## Estimate Std. Error t value Pr(>|z|)
## (Intercept) 1.03836 0.12055 8.613 < 2e-16 ***
## fpco2420 -0.04691 0.11022 -0.426 0.670
## fpco2680 0.03247 0.07465 0.435 0.664
## fpco23290 0.12169 0.07752 1.570 0.116
## ftemp31 0.26414 0.06483 4.074 4.62e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) fp2420 fp2680 f23290
## fpco2420 -0.138
## fpco2680 -0.313 0.383
## fpco23290 -0.330 0.294 0.529
## ftemp31 -0.176 -0.379 -0.087 0.089
Figure 3
Figure 3. Assessment of physiological plasticity of (A) S. siderea, (B) P. strigosa, and (C) P. astreoides in experimental treatments and by natal reef environment. Higher values represent greater plasticity in coral holobiont samples. pCO2 treatment is depicted by color and shape (300 \(\mu\)atm light purple, circle; 420 \(\mu\)atm dark purple, diamond; 680 \(\mu\)atm light orange, triangle; 3290 \(\mu\)atm dark orange, square) and temperature is represented as either closed (28\(^\circ\)C) or open (31\(^\circ\)C) symbols.
Results:
Natal reef environment (p < 0.05) and pCO2 (p < 0.05) significantly altered the physiological plasticity of S. siderea (Figure 3A; Table S3, S4). Offshore fragments exhibited a positive linear trend with increasing pCO2 while the inshore fragments appear to respond in a parabolic pattern to pCO2, with the lowest calculated distances occurring at 420 \(\mu\)atm, 31\(^\circ\)C and 680 \(\mu\)atm, 28\(^\circ\)C. Plasticity of P. strigosa and P. astreoides was not significantly altered by temperature treatment, pCO2 treatment, or natal reef environment (Figure 3B, 3C; Table S3, S4). However, P. astreoides exhibited a slight trend in the inshore fragments suggesting potentially higher plasticity with increasing pCO2 that is not seen in the offshore fragments (Figure 3C).
Supplemental Figures
Figure S1
Figure S1. Principal component analysis (PCA) of all coral holobiont physiological parameters for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides depicted by natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure S2
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = sid_pca_df_host ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 0.627 0.01852 0.5482 0.742838
## ftemp 1 2.533 0.07483 6.6463 0.003331 **
## reef 1 0.199 0.00589 0.5229 0.568288
## Residual 80 30.485 0.90076
## Total 85 33.844 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = sid_pca_df_symb ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 61056 0.20844 8.1537 0.0006662 ***
## ftemp 1 7468 0.02550 2.9920 0.0992672 .
## reef 1 24705 0.08434 9.8975 0.0019987 **
## Residual 80 199684 0.68172
## Total 85 292913 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure S2. Principal component analysis (PCA) of S. siderea coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, color intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (300 μatm light purple; 420 μatm dark purple; 680 μatm light orange; 3290 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure S3
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = dip_pca_df_host ~ fpco2 + ftemp + reef, data = p_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 0.7317 0.04116 1.2287 0.3051299
## ftemp 1 2.6047 0.14652 13.1213 0.0006662 ***
## reef 1 0.3469 0.01952 1.7478 0.1565623
## Residual 71 14.0939 0.79281
## Total 76 17.7772 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = dip_pca_df_symb ~ fpco2 + ftemp + reef, data = p_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 26899 0.02380 1.3095 0.2798135
## ftemp 1 515173 0.45590 75.2402 0.0006662 ***
## reef 1 101793 0.09008 14.8666 0.0006662 ***
## Residual 71 486140 0.43021
## Total 76 1130005 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure S3. Principal component analysis (PCA) of P. strigosa coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, color intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (300 μatm light purple; 420 μatm dark purple; 680 μatm light orange; 3290 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure S4
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = por_pca_df_host ~ fpco2 + ftemp + reef, data = a_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 1.7463 0.13595 3.4824 0.01532 *
## ftemp 1 0.4610 0.03589 2.7580 0.08195 .
## reef 1 0.2740 0.02133 1.6394 0.17988
## Residual 62 10.3638 0.80682
## Total 67 12.8452 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
##
## adonis2(formula = por_pca_df_symb ~ fpco2 + ftemp + reef, data = a_df, permutations = bootnum, method = "eu")
## Df SumOfSqs R2 F Pr(>F)
## fpco2 3 29037 0.20537 7.0360 0.0013324 **
## ftemp 1 26338 0.18628 19.1461 0.0006662 ***
## reef 1 724 0.00512 0.5263 0.4790140
## Residual 62 85288 0.60323
## Total 67 141387 1.00000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Figure S4. Principal component analysis (PCA) of P. asteroides coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, color intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (300 μatm light purple; 420 μatm dark purple; 680 μatm light orange; 3290 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure S5
Figure S5. Mean (\(\pm\)SE) physiological parameter (each row) measured for (A) S. siderea, (B) P. strigosa, (C) P. astreoides, and (D) U. tenuifolia at the completion of the 93-day experimental period.
Figure S6
Figure S6. Coral color changes over the experimental period. Representative images of fragments of (A) P. astreoides, (B) S. siderea, and (C) P. strigosa from the same colonies demonstrating change in coral color over time in either control (420 μatm; 28 °C) or warming (420 μatm; 31 °C) treatments from the start of the experiment (T0) to the end (T90).
Figure S7
Figure S7. Principal component analysis (PCA) comparing the coral holobiont of all three species at the end of the experiment depicted reef environment. Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.
Figure S8
Supplemental Tables
Table S1
Table S1. Model performance comparisons of generalized linear models (GLM) for plasticity assessments to select the best-fit model per species using the package performance (version 0.7.0). Akaike information criterion (AIC) was used to select the best-fit model per species. The performance score computes indices of model performance for all models per species at once for comparison across models.| Model formula | AIC | BIC | Conditional R2 | Marginal R2 |
|---|---|---|---|---|
| Siderastrea Siderea | ||||
| reef environment * pCO2 + temperature + (1 | colony) | 218.8 | 243.5 | 0.5059 | 0.3225 |
| reef environment * pCO2 * temperature + (1 | colony) | 223.2 | 259.2 | 0.5445 | 0.3656 |
| reef environment * (pCO2 + temperature) + (1 | colony) | 220.1 | 247.1 | 0.5115 | 0.3288 |
| reef environment + pCO2 + temperature + (1 | colony) | 221.6 | 239.6 | 0.4419 | 0.2535 |
| pCO2 + temperature + (1 | colony) | 222.1 | 237.8 | 0.3698 | 0.0882 |
| reef environment + pCO2 * temperature + (1 | colony) | 225.6 | 248.1 | 0.4421 | 0.2534 |
| Pseudodiploria strigosa | ||||
| reef environment * pCO2 * temperature + (1 | colony) | 105.6 | 121.5 | 0.3969 | 0.3170 |
| reef environment * pCO2 * temperature + (1 | colony)7 | 99.8 | 109.6 | 0.2918 | 0.2233 |
| reef environment * pCO2 + temperature + (1 | colony) | 100.8 | 111.8 | 0.3093 | 0.2614 |
| reef environment + pCO2 * temperature + (1 | colony) | 101.6 | 112.6 | 0.2784 | 0.2378 |
| Porites astreoides | ||||
| pCO2 + temperature + (1 | colony) | 97.5 | 104.8 | 0.2320 | 0.1880 |
| reef environment * pCO2 + temperature + (1 | colony) | 145.9 | 167.8 | 0.5212 | 0.1950 |
| reef environment * (pCO2 + temperature) + (1 | colony) | 147.9 | 171.8 | 0.5217 | 0.1952 |
| reef environment * pCO2 * temperature + (1 | colony) | 153.1 | 182.9 | 0.5273 | 0.1994 |
| reef environment + pCO2 + temperature + (1 | colony) | 142.3 | 158.2 | 0.4988 | 0.1738 |
| pCO2 + temperature + (1 | colony) | 140.4 | 154.4 | 0.4853 | 0.1469 |
| reef environment + pCO2 * temperature + (1 | colony) | 146.2 | 166.1 | 0.4995 | 0.1741 |
Table S2
Table S2. PERMANOVA model output from each species using the adonis2 function with 1500 iterations.| Df | Sum of Squares | R2 | F | P-value | |
|---|---|---|---|---|---|
| Siderastrea Siderea | |||||
| pCO2 | 3 | 61072 | 0.208 | 8.15 | 0.00067 |
| temperature | 1 | 7471 | 0.025 | 2.99 | 0.09127 |
| reef environment | 1 | 24705 | 0.084 | 9.89 | 0.00133 |
| Residual | 80 | 199740 | 0.682 | ||
| Total | 85 | 292988 | 1.000 | ||
| Pseudodiploria strigosa | |||||
| reef environment | 1 | 97850 | 0.087 | 14.29 | 0.00067 |
| temperature | 1 | 515604 | 0.456 | 75.29 | 0.00067 |
| pCO2 | 3 | 30444 | 0.027 | 1.48 | 0.23651 |
| Residual | 71 | 486202 | 0.430 | ||
| Total | 76 | 1130099 | 1.000 | ||
| Porites astreoides | |||||
| reef environment | 1 | 157 | 0.001 | 0.11 | 0.74151 |
| temperature | 1 | 25414 | 0.180 | 18.47 | 0.00067 |
| pCO2 | 3 | 30537 | 0.216 | 7.40 | 0.00067 |
| Residual | 62 | 85309 | 0.603 | ||
| Total | 67 | 141417 | 1.000 | ||
Table S3
Table S3. GLMM output from plasticity assessments for each species. The intercept of each model was set as 300 \(\mu\)atm, 28\(^\circ\)C, and inshore reef environment.| Estimate | Standard error | Statistic | P-value | |
|---|---|---|---|---|
| Siderastrea Siderea | ||||
| Intercept | 1.085 | 0.172 | 6.30 | 0.000 |
| reef environment (offshore) | -0.058 | 0.248 | -0.24 | 0.814 |
| pCO2 | 0.335 | 0.173 | 1.94 | 0.053 |
| pCO2 | 0.210 | 0.131 | 1.60 | 0.109 |
| pCO2-extreme | 0.419 | 0.132 | 3.17 | 0.002 |
| temperature (31C) | 0.003 | 0.076 | 0.04 | 0.967 |
| reef environment (offshore) pCO2 | -0.704 | 0.239 | -2.95 | 0.003 |
| reef environment (offshore) pCO2 | -0.409 | 0.197 | -2.08 | 0.037 |
| reef environment (offshore) pCO2-extreme | -0.278 | 0.191 | -1.45 | 0.146 |
| Pseudodiploria strigosa | ||||
| Intercept | 1.279 | 0.148 | 8.66 | 0.000 |
| pCO2 | -0.338 | 0.193 | -1.75 | 0.080 |
| pCO2-extreme | -0.059 | 0.187 | -0.31 | 0.753 |
| temperature (31C) | 0.227 | 0.173 | 1.31 | 0.190 |
| Porites astreoides | ||||
| Intercept | 1.038 | 0.121 | 8.61 | 0.000 |
| pCO2 | -0.047 | 0.110 | -0.43 | 0.670 |
| pCO2 | 0.032 | 0.075 | 0.44 | 0.664 |
| pCO2-extreme | 0.122 | 0.078 | 1.57 | 0.116 |
| temperature (31C) | 0.264 | 0.065 | 4.07 | 0.000 |
Table S4
Table S4. PERMANOVA model output across species using the adonis2 function with 1500 iterations.| Df | Sum of Squares | R2 | F | P-value | |
|---|---|---|---|---|---|
| pCO2 | 3 | 149393 | 0.038 | 8.24 | 0.00067 |
| temperature | 1 | 17313 | 0.004 | 2.87 | 0.09327 |
| reef environment | 1 | 58058 | 0.015 | 9.61 | 0.00466 |
| species | 2 | 1642613 | 0.423 | 135.91 | 0.00067 |
| temperature:species | 2 | 553351 | 0.143 | 45.78 | 0.00067 |
| pCO2:species | 6 | 90865 | 0.023 | 2.51 | 0.02398 |
| reef environment:species | 2 | 77259 | 0.020 | 6.39 | 0.00400 |
| Residual | 214 | 1293204 | 0.333 | ||
| Total | 231 | 3882055 | 1.000 |
Table S5
Table S5. PERMANOVA model output of coral host or algal symbiont physiology per species using the adonis2 function with 1500 iterations depicted in Figures S2-S4.| Df | Sum of Squares | R2 | F | P-value | Df | Sum of Squares | R2 | F | P-value | |
|---|---|---|---|---|---|---|---|---|---|---|
| Siderastrea Siderea | ||||||||||
| pCO2 | 3 | 1 | 0.019 | 0.55 | 0.74284 | 3 | 61056 | 0.208 | 8.15 | 0.00067 |
| temperature | 1 | 3 | 0.075 | 6.65 | 0.00333 | 1 | 7468 | 0.025 | 2.99 | 0.09927 |
| reef environment | 1 | 0 | 0.006 | 0.52 | 0.56829 | 1 | 24705 | 0.084 | 9.90 | 0.00200 |
| Residual | 80 | 30 | 0.901 | 80 | 199684 | 0.682 | ||||
| Total | 85 | 34 | 1.000 | 85 | 292913 | 1.000 | ||||
| Pseudodiploria strigosa | ||||||||||
| pCO2 | 3 | 1 | 0.041 | 1.23 | 0.30513 | 3 | 26899 | 0.024 | 1.31 | 0.27981 |
| temperature | 1 | 3 | 0.147 | 13.12 | 0.00067 | 1 | 515173 | 0.456 | 75.24 | 0.00067 |
| reef environment | 1 | 0 | 0.020 | 1.75 | 0.15656 | 1 | 101793 | 0.090 | 14.87 | 0.00067 |
| Residual | 71 | 14 | 0.793 | 71 | 486140 | 0.430 | ||||
| Total | 76 | 18 | 1.000 | 76 | 1130005 | 1.000 | ||||
| Porites astreoides | ||||||||||
| pCO2 | 3 | 2 | 0.136 | 3.48 | 0.01532 | 3 | 29037 | 0.205 | 7.04 | 0.00133 |
| temperature | 1 | 0 | 0.036 | 2.76 | 0.08195 | 1 | 26338 | 0.186 | 19.15 | 0.00067 |
| reef environment | 1 | 0 | 0.021 | 1.64 | 0.17988 | 1 | 724 | 0.005 | 0.53 | 0.47901 |
| Residual | 62 | 10 | 0.807 | 62 | 85288 | 0.603 | ||||
| Total | 67 | 13 | 1.000 | 67 | 141387 | 1.000 | ||||
Session information
Session information from the last run date on 2021-06-29:
## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] rcompanion_2.4.1 car_3.0-10 carData_3.0-4
## [4] png_0.1-7 MASS_7.3-53 performance_0.7.0
## [7] wesanderson_0.3.6 RColorBrewer_1.1-2 gridGraphics_0.5-1
## [10] corrplot_0.84 Hmisc_4.4-2 Formula_1.2-4
## [13] survival_3.2-7 magick_2.5.2 ggpubr_0.4.0
## [16] vroom_1.3.2 lmerTest_3.1-3 lme4_1.1-26
## [19] Matrix_1.3-2 kableExtra_1.3.1 finalfit_1.0.2
## [22] ggfortify_0.4.11-9009 cowplot_1.1.1 Rmisc_1.5
## [25] shiny_1.5.0 vegan_2.5-7 lattice_0.20-41
## [28] permute_0.9-5 forcats_0.5.0 stringr_1.4.0
## [31] purrr_0.3.4 tibble_3.0.4 tidyverse_1.3.0
## [34] plotly_4.9.3 openxlsx_4.2.3 corrgram_1.13
## [37] tidyr_1.1.2 ggbiplot_0.55 scales_1.1.1
## [40] plyr_1.8.6 dplyr_1.0.2 ggplot2_3.3.3
## [43] broom_0.7.3 readr_1.4.0 knitr_1.33
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.1.0 htmlwidgets_1.5.3 TSP_1.1-10
## [4] munsell_0.5.0 codetools_0.2-18 effectsize_0.4.1
## [7] statmod_1.4.35 withr_2.4.2 colorspace_2.0-0
## [10] highr_0.8 rstudioapi_0.13 stats4_3.6.3
## [13] DescTools_0.99.41 ggsignif_0.6.0 labeling_0.4.2
## [16] bit64_4.0.5 farver_2.0.3 vctrs_0.3.6
## [19] generics_0.1.0 TH.data_1.0-10 xfun_0.22
## [22] R6_2.5.0 seriation_1.2-9 assertthat_0.2.1
## [25] promises_1.1.1 multcomp_1.4-15 nnet_7.3-14
## [28] rootSolve_1.8.2.1 gtable_0.3.0 multcompView_0.1-8
## [31] lmom_2.8 sandwich_3.0-0 rlang_0.4.11
## [34] splines_3.6.3 rstatix_0.6.0 lazyeval_0.2.2
## [37] checkmate_2.0.0 yaml_2.2.1 abind_1.4-5
## [40] modelr_0.1.8 backports_1.2.1 httpuv_1.5.5
## [43] tools_3.6.3 ellipsis_0.3.1 ggridges_0.5.3
## [46] Rcpp_1.0.5 base64enc_0.1-3 rpart_4.1-15
## [49] zoo_1.8-8 haven_2.3.1 ggrepel_0.9.0
## [52] cluster_2.1.0 fs_1.5.0 magrittr_2.0.1
## [55] data.table_1.13.6 lmtest_0.9-38 reprex_0.3.0
## [58] mvtnorm_1.1-1 matrixStats_0.57.0 hms_1.0.0
## [61] mime_0.10 evaluate_0.14 xtable_1.8-4
## [64] rio_0.5.16 jpeg_0.1-8.1 readxl_1.3.1
## [67] gridExtra_2.3 compiler_3.6.3 mice_3.13.0
## [70] crayon_1.3.4 minqa_1.2.4 htmltools_0.5.1
## [73] mgcv_1.8-33 later_1.1.0.1 libcoin_1.0-8
## [76] expm_0.999-6 Exact_2.1 lubridate_1.7.9.2
## [79] DBI_1.1.0 dbplyr_2.0.0 see_0.6.2
## [82] boot_1.3-25 cli_2.5.0 parallel_3.6.3
## [85] insight_0.13.1 pkgconfig_2.0.3 registry_0.5-1
## [88] numDeriv_2016.8-1.1 coin_1.4-1 foreign_0.8-75
## [91] xml2_1.3.2 foreach_1.5.1 webshot_0.5.2
## [94] rvest_0.3.6 digest_0.6.27 parameters_0.10.1
## [97] rmarkdown_2.6 cellranger_1.1.0 htmlTable_2.1.0
## [100] nortest_1.0-4 gld_2.6.2 curl_4.3.1
## [103] modeltools_0.2-23 nloptr_1.2.2.2 lifecycle_1.0.0
## [106] nlme_3.1-151 jsonlite_1.7.2 viridisLite_0.3.0
## [109] pillar_1.4.7 fastmap_1.0.1 httr_1.4.2
## [112] glue_1.4.2 bayestestR_0.8.0 zip_2.1.1
## [115] iterators_1.0.13 bit_4.0.4 class_7.3-17
## [118] stringi_1.5.3 latticeExtra_0.6-29 e1071_1.7-4